Data engineer

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• Develop, operate, optimize, test, and maintain the data warehouse, including ETL/ELT process development, cube development, database/performance administration, and dimensional table design
• Drive the full life-cycle of back-end development for the data warehouse
• Identify, design, and implement internal process improvements - redesigning infrastructure for scalability, optimizing data delivery, and automating manual processes
• Define data retention policies
• Build analytical tools that leverage the data pipeline to deliver actionable insight into key business metrics (operational efficiency, customer acquisition, etc.)
• Select and integrate tools for monitoring, managing, alerting on, and improving database performance
• Develop and implement automated processes to ensure uninterrupted database updates and correction of vulnerabilities
• Assemble large, complex datasets that meet functional and non-functional business requirements

• 5+ years of experience or 5+ completed projects
• Advanced SQL and query optimization, with proficiency across popular database variations
• Python for data engineering and automation
• Cloud data platforms: Snowflake and/or Databricks
• Cloud services: AWS and/or Azure
• Data transformation and modeling with DBT
• ETL/ELT pipeline design, development, and maintenance
• Apache Spark (PySpark preferred)
• Workflow orchestration using Apache Airflow, Dagster, or another widely adopted orchestrator
• Relational database design and performance tuning (PostgreSQL, MySQL, SQL Server, Oracle, etc.)
• Data warehousing concepts and dimensional modeling
• Data management fundamentals: data modeling, data quality, metadata management, data warehouse/lake patterns, distributed systems
• Version control using Git and CI/CD practices
• Data governance, data quality, lineage, and observability practices
• Security and access control implementation in cloud data platforms
• Будет плюсом: Apache Kafka, Apache Flink, Apache Beam; Terraform, Kubernetes, Docker; Apache Iceberg, Delta Lake, or Apache Hudi; Real-time and event-driven architectures; AWS Glue, Amazon MWAA, Azure Data Factory; Data Mesh and Data Product concepts; Machine learning data pipelines, feature stores, or AI development experience; Streaming analytics and Change Data Capture (CDC) solutions (e.g., Debezium)

• Vacation: As per the laws of your country. We do ask you to take a proper rest
• Health insurance: We help you to take out an insurance policy for you and your loved ones
• Sick pay: 10 days without a doctor's note, afterwards - as per the laws of your country
• Time off for state holidays: According to the official calendar, regardless of the client’s schedule
• Pleasant environment: Two large corporate parties and many small get-togethers for colleagues
• Comfort service: Solving technical and everyday problems at work
• The benefits package may vary depending on the region and the type of contract